Last Updated: September 5, 2023

If the majority of people come and leave your website without completing the actions/goals you desire then you can’t have a good conversion rate.

But what if people come and leave your website from the landing page but still complete your desired goals.

How will you determine such conversions?

In other words, you are getting conversions through bounced sessions. 

But since it is a bounced session (visit) you have no idea how valuable your bounced sessions could be.

Generally, a high bounce rate indicates that the landing page is not relevant to your users.

But what if the landing page is relevant to your users but it gets 100% bounce rate majority of the time because it satisfies visitors’ query and there is no need to explore your website any further?

This is usually the case with content-rich websites like blogs, news site, publishing sites, etc.

Why do you need adjusted bounce rate?

People come to your site, consume contents and then leave the website from the landing page without browsing any further.

Since Google analytics by default can report time spent on a webpage only when a visitor navigates to another web page on the site, we can never know how much time is spent on a particular page and whether 100% bounce rate is good or bad.

We often do experimentation and testing of a landing page on the basis of its bounce rate.

High bounce rate is bad. Something is wrong with the page.

That’s the general opinion of marketers/analysts.

But what if nothing is wrong with the page and in fact, you bounce rate calculations are all wrong.

Imagine how dangerous it could be to take business decisions on the basis of a faulty bounce rate metric.

The landing pages you think stink, don’t stink in the first place and yet you continue to optimize them.

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What should not be considered a bounce?

Before we fix the bounce rate of our website, we need to decide what should not be considered as a bounce.

“When a person completes a goal or a transaction on your website then his/her visit should not be counted as a bounce even if that visit is a single page visit.”

This is because our primary reason for running a website is to get conversions and transactions and not to optimize bounce rates.

Once we have done this we have achieved our goals. No crappy bounce rate should mislead us.

Now the next question that comes up is

How can we determine the users’ behavior that should not be considered a bounce?

For this, follow the steps below:

Step-1:  Head to the Engagement report (under Audience > Behavior) in your Google Analytics main view.

Step-2: Set date range of your report to the last 4 months.

Step-3: Apply the advanced segment ‘Sessions with Conversions’

If you look at the screenshot above you can easily determine that majority of conversions take place when visitors spend more than 1 minute (61 – 180 seconds +) on the website.

So if I want a user to convert on the website, I need to make him stay at least for 1 minute on my website.

Because if he stays that long, then it is highly likely that he will convert.

I call this engagement profitable engagement because it leads to conversions.

If you run/manage an e-commerce website then you should also apply another advanced segment called ‘Sessions with transactions’ to determine profitable engagement:

From the report above, we can conclude that majority of conversions and transactions take place when visitors spend more than 3 minutes on the website.

So if I want a user to convert on the website, I need to make him stay at least for 3 minutes on my website.

Because if he stays that long, then it is highly likely, that he will convert.

3 minutes visit duration is pretty much standard but it may be different in case of your website/niche.

So I would strongly suggest you to determine the minimum time it takes for majority of your website users to profitably engage with your website.

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Adjusting bounce rate in Google Analytics

Once you have determined the minimum time required to profitably engage with your website users, you need to make some adjustment to your bounce rate, so that you can see true bounce rate metric in your Google Analytics report.

Remember, the bounce rate metric will still not be 100% accurate (more about it later) but would be still significantly better than the bounce rate you currently see in your reports.

Add following line of code to your Google Analytics Tracking code on each page of your website:

setTimeout(“ga(‘send’,’event’,’Profitable Engagement’,’time on page more than 3 minutes’)”,180000);

The complete Google Analytics Tracking Code may look like the following:

<script>
(function(i,s,o,g,r,a,m){i[‘GoogleAnalyticsObject’]=r;i[r]=i[r]||function(){
(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
})(window,document,’script’,’//www.google-analytics.com/analytics.js’,’ga’);

ga(‘create’, ‘UA-XXXX-XX‘, ‘auto’);
ga(‘require’, ‘linkid’, ‘linkid.js’);
ga(‘require’, ‘displayfeatures’);
ga(‘send’, ‘pageview’);
setTimeout(“ga(‘send’,’event’,’Profitable Engagement’,’time on page more than X minutes‘)”,XXXXX);
</script>

#1 Replace the ‘UA-XXXX-XX’ with your Google Analytics property number

#2 Replace X minutes with the minimum time required to profitably engage with your website users in minutes.

#3 Replace XXXXX with the minimum time required to profitably engage with your website users in milliseconds.

The setTimeout() is a JavaScript function (method) which waits for a specified number of milliseconds before it executes the specified function.

Syntax: setTimeout(“javascript function”,milliseconds);

The javascript function that I am using for the setTimeout() method is:

ga(‘send’,’event’,’Profitable Engagement’,’time on page more than X minutes’)

Through this function, I have set up:

#1 Event category: Profitable Engagement

#2 Event Action: Time on page more than X minutes

However, GA will not send the event tracking data to its server unless X minutes have elapsed because of the setTimeout method.

So long story short, I fire an event on a web page when more than 3 minutes have elapsed.

This will give me a good idea of whether or not visitors are profitably engaging with contents on the site despite their single page visits.

So if visitors are profitably engaging with the site contents then I will treat their visits as non-bounce visit.

Remember the geek definition of bounce rate:

Bounce rate is the percentage of single page visits/sessions in which only one GIF request is sent to the Google Analytics server.

So if you want to make a visit a non-bounce visit then you need to pass more than one GIF request to the Google Analytics server within a single session.

Every Google analytics tracking code sends at least one GIF request to the Google Analytics server.

If your Google Analytics tracking code also fires an event tracking code then two GIF requests will be sent to the Google Analytics server in a single session.

Since more than one GIF request is sent to the Google Analytics server in a single session, the visit will no longer be treated as bounce visit by Google Analytics.

What will happen next?

Once you have adjusted your bounce rate metric by editing your Google Analytics Tracking code, the overall bounce rate of your website will most probably go down within few days and you will see a bounce rate which is a better representative of true bounce rate.

After adjustment, the bounce rate of my website went down from the whopping 78.72% to 27.74% within a week.

That’s a massive difference. Isn’t it? I will take different marketing decision on the basis of 27% bounce rate than on the basis of 78% bounce rate.

Tracking conversions through bounced sessions

If people are converting in a single page visit then you need to track this behavior. But how?

One answer is tracking events as goals.

For example, let us say that when a visitor spends more than 3 minutes on your website he/she is most likely to convert.

So I can configure the setTimeout() method to capture the event once a visitor has spend say 3 or more minutes on a web page.

The code for this is the same as above:

setTimeout(“ga(‘send’,’event’,’Profitable Engagement’,’time on page more than 3 minutes’)”,180000);

Here ‘profitable engagement’ is the event category, ‘time on page more than 3 minutes’ is the event action.

To know more about event tracking in Google Analytics, check out this article: Event Tracking in Google Analytics.

Set up this event as a goal in your analytics view with following specifications:

 Once you have set up this goal and starts collecting goals data you will see a report (Conversions > Goals > Goal URL) like the one below:

How to measure and audit the correct bounce rate

If you want to measure and audit your correct bounce rate, you need to understand what is causing a high bounce rate. Once you find the actual reason for the bounce rate it’s easy to lower it down by carrying out corrective measures.

The following are the best ways to segment data to understand what is causing a high bounce rate.

#1: Segmenting by Age:

In the Google Analytics menu, If you go to Audience>> Demographics >> Age, you can find the bounce rate metrics according to age range.

You can see from the above image that bounce rate is on the higher side for age group 55 to 65+. If senior citizens are part of your targeted audience group, you might think of improving your website elements to suit their needs (probably more visible and bigger call to action elements)

#2: Segmenting by Gender

In a similar fashion, you can check bounce rate by segmenting it by gender. Just go to the Google Analytics console and click on Audience>> Demographics>> Gender

As you can see from the image above, bounce rate is high for female users compared to male users. This might be due to the content offered on the website and the color combination used which impacts user behavior and purchase activities.

#3: Segmenting by Affinity Category/ In Market Segment

Affinity category is the users who can be your potential customers in the purchase funnel, whilst In Market segment are the users who are more likely to convert.

You can see from the below image that Home and Garden has the highest bounce rate. It indicates that your content and images are attracting users that can relate to the category but they don’t find anything interesting in the content and hence leading to a higher bounce rate. In this case, it’s your decision, based on your website objectives, as to whether you change the content or not.

#4: Segmenting by Country

You can access the report in your Google Analytics console by clicking on Audience >> Geo >> Location. Segmenting by country will give you an exact idea about bounce rate by country and means you can adjust your marketing strategy and content preference as per users in those countries.

From the following image, you can see that, other than the United States, all countries have a higher bounce rate. If any higher bounce rate country is in your targeted location you may need to think of adjusting your content and images according to the country.

#5: Segmenting by User Type:

It’s obvious that for new users bounce rate will be high because they are visiting for the first time but you might have to look at your content strategy if the returning visitor bounce rate is higher compared to new visitors.

You can further drill down into the users along with their source and medium using secondary dimension.

In the below image you can see that the traffic coming from direct source has a higher bounce rate for returning visitors compared to new visitors. This might indicate that the content strategy for returning visitors should be unique with some fresh content in order to reduce bounce rate.

#6 Segmenting By Device Category

Device category plays an important role in terms of determining bounce rate. Device category gives you an insight into how individual devices are delivering content to individual users and their performance.

You can access the report by going to your analytics console and then clicking on Audience >> Mobile >> Overview.

As you can see from the below image, mobile and tablet devices have a higher bounce rate compared to desktop. You might think of changing the mobile and tablet device website view and improve its performance to reduce bounce rate and gain more conversions.

You can further drill down to find individual performance and can change your marketing strategy according to the device type used by most users.

#7: Segmenting by Browser Type:

If you see a higher bounce rate for a particular type of browser, it means you haven’t configured your website to deliver the best user experience for that corresponding browser.

From the below image you can see that there is a higher bounce rate for Safari, Internet Explorer, etc.

You can further drill down to browser version to get an in-depth analysis of bounce rate. The following image shows the details of which browser versions perform worst.

#8: Segmenting by Acquisition:

If you are running multiple advertising campaigns like Google Ads, remarketing, social media, email, etc. and would like to know campaign performance you can go to Google Analytics console and click on Acquisition >> All Traffic >> Source Medium.

From the above image, you can see that traffic coming from Google CPC, Double Click, Instagram and Facebook referrals have a higher bounce rate. This indicates that either your ad content is not relevant to the content on your website or vice versa. In this case, you can use the bounce rate metrics to optimize your campaign by doing the necessary changes.

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Adjusting the bounce rate (the advanced way)

Once you know how to audit and measure your bounce rate on the website the next step is to get bounce rate as accurate as technically possible, I would suggest that you determine profitable engagement duration for each section or content type of your website and then adjust your bounce rate accordingly.

What that means, you need to add different tracking code to different pages on your website which record bounce rate differently.

If you are not using Google Tag Manager, then it is going to be very time consuming to track bounce rate per website section.

But that’s the only way to get bounce rate as accurate as technically possible.

People spend different amount of time on different type of contents.

For example you can’t expect visitors to spend 3 or more minutes on a ‘contact us’ page, support page or ‘about us’ page or on a small infographic or article.

So you need to adjust your bounce rate for different sections or type of contents on your site accordingly.

In the end it all depends upon how accurate you want your bounce rate calculations to be and how much bounce rate impact your marketing decisions.

To learn about adjusting bounce rate in Google Analytics via Google Tag Manager, check out this article: Adjusting Bounce Rate via Google Tag Manager

Other articles related to Google Analytics Bounce Rate

• Bounce Rate in Google Analytics Explained
• What is a good bounce rate in Google Analytics? (the acceptable bounce rate)
• What is a bad bounce rate in Google Analytics?
• How does Google Analytics calculate bounce rate? (formula for bounce rate calculation)
• 10 main reasons for high Bounce Rate in Google Analytics
• Reason of very low bounce rate in Google Analytics
• 100% Bounce Rate in Google Analytics Explained
• Is high Google Analytics Bounce Rate always bad?
• 0% Bounce Rate in Google Analytics Explained
• 11 Methods to Reduce Bounce Rate in Google Analytics
• Difference between Bounce Rate and Exit Rate in Google Analytics
• Adjusting Bounce Rate via Google Tag Manager